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https://github.com/kjanat/livedash-node.git
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feat: Implement structured message parsing and display in MessageViewer component
- Added MessageViewer component to display parsed messages in a chat-like format. - Introduced new Message table in the database to store individual messages with timestamps, roles, and content. - Updated Session model to include a relation to parsed messages. - Created transcript parsing logic to convert raw transcripts into structured messages. - Enhanced processing scheduler to handle sessions with parsed messages. - Updated API endpoints to return parsed messages alongside session details. - Added manual trigger commands for session refresh, transcript parsing, and processing. - Improved user experience with color-coded message roles and timestamps in the UI. - Documented the new scheduler workflow and transcript parsing implementation.
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docs/scheduler-workflow.md
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docs/scheduler-workflow.md
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# Scheduler Workflow Documentation
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## Overview
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The LiveDash system has two main schedulers that work together to fetch and process session data:
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1. **Session Refresh Scheduler** - Fetches new sessions from CSV files
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2. **Processing Scheduler** - Processes session transcripts with AI
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## Current Status (as of latest check)
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- **Total sessions**: 107
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- **Processed sessions**: 0
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- **Sessions with transcript**: 0
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- **Ready for processing**: 0
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## How the `processed` Field Works
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The ProcessingScheduler picks up sessions where `processed` is **NOT** `true`, which includes:
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- `processed = false`
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- `processed = null`
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**Query used:**
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```javascript
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{ processed: { not: true } } // Either false or null
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```
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## Complete Workflow
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### Step 1: Session Refresh (CSV Fetching)
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**What it does:**
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- Fetches session data from company CSV URLs
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- Creates session records in database with basic metadata
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- Sets `transcriptContent = null` initially
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- Sets `processed = null` initially
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**Runs:** Every 30 minutes (cron: `*/30 * * * *`)
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### Step 2: Transcript Fetching
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**What it does:**
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- Downloads full transcript content for sessions
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- Updates `transcriptContent` field with actual conversation data
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- Sessions remain `processed = null` until AI processing
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**Runs:** As part of session refresh process
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### Step 3: AI Processing
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**What it does:**
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- Finds sessions with transcript content where `processed != true`
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- Sends transcripts to OpenAI for analysis
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- Extracts: sentiment, category, questions, summary, etc.
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- Updates session with processed data
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- Sets `processed = true`
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**Runs:** Every hour (cron: `0 * * * *`)
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## Manual Trigger Commands
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### Check Current Status
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```bash
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node scripts/manual-triggers.js status
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```
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### Trigger Session Refresh (Fetch new sessions from CSV)
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```bash
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node scripts/manual-triggers.js refresh
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```
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### Trigger AI Processing (Process unprocessed sessions)
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```bash
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node scripts/manual-triggers.js process
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```
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### Run Both Schedulers
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```bash
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node scripts/manual-triggers.js both
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```
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## Troubleshooting
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### No Sessions Being Processed?
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1. **Check if sessions have transcripts:**
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```bash
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node scripts/manual-triggers.js status
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```
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2. **If "Sessions with transcript" is 0:**
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- Sessions exist but transcripts haven't been fetched yet
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- Run session refresh: `node scripts/manual-triggers.js refresh`
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3. **If "Ready for processing" is 0 but "Sessions with transcript" > 0:**
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- All sessions with transcripts have already been processed
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- Check if `OPENAI_API_KEY` is set in environment
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### Common Issues
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#### "No sessions found requiring processing"
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- All sessions with transcripts have been processed (`processed = true`)
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- Or no sessions have transcript content yet
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#### "OPENAI_API_KEY environment variable is not set"
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- Add OpenAI API key to `.env.development` file
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- Restart the application
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#### "Error fetching transcript: Unauthorized"
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- CSV credentials are incorrect or expired
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- Check company CSV username/password in database
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## Database Field Mapping
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### Before AI Processing
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```javascript
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{
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id: "session-uuid",
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transcriptContent: "full conversation text" | null,
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processed: null,
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sentimentCategory: null,
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questions: null,
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summary: null,
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// ... other fields
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}
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```
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### After AI Processing
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```javascript
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{
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id: "session-uuid",
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transcriptContent: "full conversation text",
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processed: true,
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sentimentCategory: "positive" | "neutral" | "negative",
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questions: '["question 1", "question 2"]', // JSON string
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summary: "Brief conversation summary",
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language: "en", // ISO 639-1 code
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messagesSent: 5,
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sentiment: 0.8, // Float value (-1 to 1)
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escalated: false,
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forwardedHr: false,
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category: "Schedule & Hours",
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// ... other fields
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}
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```
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## Scheduler Configuration
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### Session Refresh Scheduler
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- **File**: `lib/scheduler.js`
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- **Frequency**: Every 30 minutes
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- **Cron**: `*/30 * * * *`
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### Processing Scheduler
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- **File**: `lib/processingScheduler.js`
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- **Frequency**: Every hour
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- **Cron**: `0 * * * *`
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- **Batch size**: 10 sessions per run
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## Environment Variables Required
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```bash
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# Database
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DATABASE_URL="postgresql://..."
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# OpenAI (for processing)
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OPENAI_API_KEY="sk-..."
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# NextAuth
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NEXTAUTH_SECRET="..."
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NEXTAUTH_URL="http://localhost:3000"
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```
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## Next Steps for Testing
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1. **Trigger session refresh** to fetch transcripts:
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```bash
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node scripts/manual-triggers.js refresh
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```
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2. **Check status** to see if transcripts were fetched:
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```bash
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node scripts/manual-triggers.js status
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```
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3. **Trigger processing** if transcripts are available:
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```bash
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node scripts/manual-triggers.js process
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```
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4. **View results** in the dashboard session details pages
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